"A server for accessing and managing local file system" matching MCP servers:

Provides secure file read and write operations within a sandboxed directory, allowing AI assistants to safely create, modify, and access files without risk of accessing the broader file system.

A comprehensive MCP (Model Context Protocol) server for file system operations, providing Claude and other AI assistants with access to local files and directories.

A secure, sandboxed file system server that enables reading, writing, searching, and managing files through MCP-compatible AI clients with path traversal protection and size limits.

An agentic file-system assistant that lets users read, write, list, and search local files through natural language, using a LangChain agent with an Ollama LLM backed by a FastMCP server.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Provides tools to check disk usage and search files by keyword on the local system.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

Provides tools for searching and reading local files, supporting metadata filters, PDF full-text keyword search, and sandboxed file access.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables local web crawling and scraping through MCP, providing tools to fetch pages as Markdown, extract structured data with CSS selectors, and capture full-page screenshots while managing a shared browser instance.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

A secure file server for AI assistants that provides comprehensive file operations and text manipulation with configurable access levels and multiple connection modes.

Enables interaction with the local file system and retrieval of system information. Provides tools for listing directories, reading files, getting current time, and basic greeting functionality.

A memory MCP server with a dual-storage system using ChromaDB and NetworkX DiGraph, enabling efficient data management and integration with IDEs like Cursor and VSCode for enhanced research and note organization.

A Model Context Protocol server that provides secure, sandboxed file system operations including reading, writing, and managing files within a configurable base directory. It features robust path traversal protection to ensure all file interactions remain confined to a safe, restricted environment.

A hybrid REST + MCP file server for managing files with large file streaming support, enabling AI agents and web frontends to perform file operations via MCP tools and REST APIs.

This server provides an interface for performing basic file system operations such as navigation, reading, writing, and file analysis, allowing users to manage directories and files efficiently.

Enables local analysis of unstructured documents (PDF, DOCX, PPTX, SVG, PNG) by extracting text and structure with citation anchors, and verifies summaries against source material before a human approves saving a report.

An MCP server that exposes filesystem operations — listing directories, reading, writing, and searching files — as tools an LLM can discover and invoke at runtime.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.